Correlation/Regression

David C. Howell

Correlation and regression is discussed in a number of different
examples, illustrated a variety of uses.

Sethi and Seligman's (1993) study of
the correlates of optimism and religious fundamentalism looks at both simple and multiple
correlation and regression. In particular, it looks at the averaging of correlation
coefficients.

For those who would like to generate two variables with a
specified correlation between them, there is a very simple procedure that can be applied
with any statistical package.

If you want a whole set of variables with a specified set of correlations, check out the
response that David Nichols wrote in response to
such an inquiry. An SPSS program that implements his suggestion is available at CorrGen2.html.

A lab exercise investigating correlation (as well as t
and power) is useful. It assumes SPSS, but the program could be rewritten for a different
software package. The lab is not really a correlation lab, but it h as a program that will
be useful and it has elements of correlation.

A good demonstration of how variable sample correlation coefficients can be can be found
at SampDistCorr.html. It shows students that variability
is part of the nature of things.

If you are correlating variables (such as scores from twins or gay
partners) where there is no ordering within a pair (e.g. either twin could
be considered twinA or twinB), you want an intraclass
correlation coefficient.

The sampling distribution of regression coefficients (b and b)
are described in a document named SampDistRegCoeff.pdf.